Ameen, Fatimah Nadhim (2025) Investigation on Dynamic PV Array Reconfiguration Performance Enhancement Under Non-Uniform Partial Shading Conditions. PhD thesis, Miskolci Egyetem.
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Text (Dissertation)
Fatimah_Nadhim_Ameen_ert_doi.pdf - Published Version Download (15MB) | Preview |
Abstract
The increasing demand for renewable energy has driven extensive research into optimizing photovoltaic (PV) systems to ensure reliable power generation under varying environmental conditions. Partial shading, temperature variations, and electrical mismatch losses significantly affect PV system efficiency, leading to power losses and multiple peaks in the power-voltage curve. To address these challenges, this research introduces a Dynamic Probabilistic Reconfiguration Algorithm (DPRA) integrated into a hierarchical PV array system, enhancing energy extraction through real-time reconfiguration and adaptive control mechanisms. The proposed system employs a hierarchical switching block (SB) architecture, incorporating microcontrollers, sensors (BH1750, DS18B20), and relays to dynamically adjust PV connections based on shading and temperature variations. A high-temperature isolation mechanism prevents thermal degradation by reducing panel temperatures from 76.45°C to 61.93°C, ensuring system reliability. The study evaluates two hierarchical reconfiguration models using MATLAB-Simulink simulations and experimental validation. Model-A features a simplified design, linking two panels per switching block, while Model-B offers an advanced reconfiguration scheme supporting Series-Parallel (SP), Bridge-Link (BL), and Total Cross-Tied (TCT) topologies. Results confirm that Model-B significantly improves PV performance, achieving power output gains of up to 81.61% and efficiency improvements of 42.13% under various shading conditions. The HLLBE algorithm dynamically redistributes irradiance across PV layers, improving efficiency by 116.6% compared to fixed TCT configurations. DPRA also reduces computational complexity by 50%, enabling faster optimization and enhanced real-time adaptability. Comparisons with Sudoku-based, Magic Square, and hybrid PSO-based configurations demonstrate the superiority of the proposed system, with power generation improvements ranging from 21.6% to 39.37% and efficiency gains between 32.39% and 42.52%. Additionally, the probabilistic optimization framework reduces hardware complexity, achieving a 79.17% reduction in switch count compared to Dynamic Electrical Structures (DES). The proposed DPRA-based hierarchical PV system supports scalability, allowing for seamless integration of additional panels without extensive rewiring, making it suitable for both residential and utility-scale solar applications. Although the initial cost for DPRA implementation is slightly higher ($688) than TCT ($591), the substantial gains in energy output, efficiency, and system longevity make it a cost-effective and scalable solution for improving PV performance. By bridging the gap between theoretical innovation and practical application, this research contributes to advancing PV technology and paves the way for scalable, intelligent systems capable of meeting the growing energy demands of a sustainable future.
| Item Type: | Thesis (PhD) |
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| Subjects: | Q Science / természettudomány > QA Mathematics / matematika > QA75 Electronic computers. Computer science / számítástechnika |
| SWORD Depositor: | Software Sword MTMT |
| Depositing User: | Software Sword MTMT |
| Date Deposited: | 13 Oct 2025 08:29 |
| Last Modified: | 13 Oct 2025 08:29 |
| URI: | https://real-phd.mtak.hu/id/eprint/2196 |
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